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GARMIN LTD: nonoperating income or expense

Nonoperating income or expense for GARMIN LTD. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All GARMIN LTD financial histories

What this measure means

Total nonoperating income or expense, which can include interest, investment results and other items. A positive value is not operating profit.

Exact concept: us-gaap:NonoperatingIncomeExpense. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2006-12-31 to 2025-12-27. The SEC response was captured on 2026-09-20.

Selected filing history

Nonoperating income or expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2024-12-292025-12-27138,459,000USD2026-02-1810-K · 0001193125-26-056028
2023-12-312024-12-28101,407,000USD2026-02-1810-K · 0001193125-26-056028
2023-01-012023-12-30108,196,000USD2026-02-1810-K · 0001193125-26-056028
2021-12-262022-12-3137,129,000USD2025-02-1910-K · 0000950170-25-022760
2020-12-272021-12-25-11,824,000USD2024-02-2110-K · 0000950170-24-017559
2019-12-292020-12-2649,170,000USD2023-02-2210-K · 0000950170-23-003566
2018-12-302019-12-2841,636,000USD2022-02-1610-K · 0000950170-22-001303
2017-12-312018-12-2944,904,000USD2021-02-1710-K · 0001564590-21-006192
2017-01-012017-12-3013,434,000USD2020-02-1910-K · 0001564590-20-005133
2015-12-272016-12-315,761,000USD2019-02-2010-K · 0001615774-19-002739
2014-12-282015-12-2617,606,000USD2018-02-2110-K · 0001615774-18-001344
2013-12-292014-12-2733,119,000USD2017-02-2210-K · 0001615774-17-000765
2012-12-302013-12-2879,526,000USD2016-02-1710-K · 0001615774-16-004243
2012-01-012012-12-2920,368,000USD2015-02-1810-K · 0001144204-15-010586
2010-12-262011-12-3130,394,000USD2014-02-1910-K · 0001144204-14-010483
2009-12-272010-12-25-59,404,000USD2013-02-2710-K · 0001144204-13-011527
2008-12-282009-12-2622,641,000USD2012-02-2910-K · 0001144204-12-012007
2007-12-302008-12-2752,349,000USD2011-02-2310-K · 0001144204-11-010358
2006-12-312007-12-2970,922,000USD2010-02-2410-K · 0001144204-10-009642

Related financial histories

Inspect the source

Entity
GARMIN LTD / CIK 0001121788
Captured
2026-09-20T07:39:57.594Z
SEC response SHA-256
f132e5d872392f477b3b4f7e7f3e558fd35c4f5bb10547a94ed208bd01156dd5

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001121788.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))